AI-Powered Academic Talent Finder 

Recruiting academic talent is a complex challenge for universities and research institutions, as conventional recruitment platforms like LinkedIn or job boards often fail to capture research-focused metrics such as publication history, citation counts, or journal rankings. These are crucial indicators of a scholar’s impact and potential but are scattered across multiple databases, making the recruitment process slow, fragmented, and resource-intensive.

To address this gap, our team is developing an AI-driven academic talent finder platform designed specifically for higher education and research organizations. The platform integrates data from trusted academic sources such as Google Scholar, Scopus, and OpenAlex, providing recruiters with verified researcher profiles that include publications, affiliations, and performance metrics. A powerful search engine with filters for expertise, h-index, and institutional background allows recruiters to quickly identify suitable candidates.

Beyond search, the platform supports bookmarking and exporting (PDF/Excel) to streamline shortlisting and reporting. Recruiters can save researchers of interest, generate structured outputs, and easily share results with decision-makers.



By combining AI-powered data extraction, robust search functionality, and a user-friendly interface, the system improves efficiency, reduces recruitment costs, and enhances transparency in academic hiring. Ultimately, it empowers institutions to discover and connect with high-impact researchers more effectively.